【作者】 高翠娟；

【导师】 祁庆生；

【作者基本信息】 山东大学 ， 发酵工程， 2010， 博士

【摘要】 酿酒酵母作为与人类关系最为密切的微生物广泛用于乙醇发酵领域。高浓度发酵能够在单位时间和体积内提高发酵终产物的浓度,成为降低乙醇发酵成本的有效途径。但在发酵初期高浓度底物(如葡萄糖)以及随后逐渐积累的乙醇所产生的各种压力,会对细胞产生毒害作用,影响发酵产量。通过研究酿酒酵母抗乙醇压力的分子机制,有助于理性设计实验以提高其在乙醇发酵的工业应用。酿酒酵母作为真核微生物,它的功能基因转录机制相对复杂,需要组装一个以RNA polⅡ为核心的转录预起始复合体(PIC),包括RNA聚合酶Ⅱ和其他的通用／基本转录因子(General/basal transcription factors, GTF’s),构成约2MDa的大分子。GTF’s对转录至关重要,通过体外分离纯化实验共分离至IJTFIIA、TFⅡB、TFⅡC、TFⅡD、TFⅡF和TFIIH六个GTF’s。其中,TFⅡD由TBP和至少14个紧密结合的TBP辅助因子(TAFs)组成的多亚基复合物,TBP特异性结合TATA元件,而TAFs直接或间接与其它核心启动子元件结合。每一个基因上游启动子部分除了TATA框之外,都还含有增强子等其他独特的序列元件,它们能够被特异性的转录激活因子识别,每个基因的表达受到多个不同的转录激活因子的共同作用。同时,转录激活因子的活性受转录信号传导途径所介导。任意时刻的细胞都是所含基因受到特定转录因子的调控而表达的结果。酵母细胞对乙醇／葡萄糖的耐受性表现为多基因控制。由于抗性机制的复杂性及其存在的动力学相互作用,大大阻碍了基于已有的分子生物学功能的代谢工程的应用,很难通过传统的方法对之改造。全局转录机制工程(Global transcription machinery engineering, gTME)技术作为一种全新的方法,它借助随机突变改造转录因子TBP (TATA binding protein)促使整个转录调控过程发生变化,在基因组水平上重建大多数基因的转录模式,从而改变或提高目标基因的转录及表达。驯化工程则是遵循自然的“工程”原理。细胞代谢网络具有很大的弹性,通过定向驯化的手段可以对代谢通量进行优化,获得性能优良的工业微生物菌种。与以DNA重组技术为基础的代谢工程不同,它将细胞作为一个整体,通过定向驯化、筛选获得表型提高的突变菌株,然后再结合高通量的分析方法,从分子水平研究表型提高的分子机制。对性能提高的突变体进行代谢通量分析和转录组学分析,利用获得的信息进一步对菌种进行定向代谢工程改造,将使人们更快速改造细胞的代谢和生理功能。同时,对细胞代谢调控的认识,也将应用于系统生物学和合成生物学的研究,使人们能更有效地控制和设计细胞工厂。驯化工程作为科学而有效的手段,它对于菌株的分子代谢过程改造和优化不失为一个很有效的补充。驯化工程除了简单的随机突变和定向选择之外,它还能进行重组,并通过多次传代进行连续的驯化。快速发展起来的全局分析方法,包括全基因组重测序、转录组分析、蛋白质组分析、代谢组分析等,有助于我们发现驯化表型的分子机制。围绕以上思路,本论文的主要研究内容如下：首先,我们尝试了gTME在酵母实验菌株W303-1A中的应用研究。采用外源低拷贝质粒表达了调控因子TBP (SPT15)的等位突变基因SPT15-300,以表达SPT15的质粒作为对照,研究了表达SPT15-300对细胞在含有乙醇／葡萄糖组合压力下的细胞生长,结果显示SPT15-300对实验菌株在压力条件下的生长表型提高并不显著,这可能与我们采用营养较为丰富的完全培养基有关。显示出SPT15-300在菌株对乙醇／葡萄糖压力响应方面的复杂性。因此,我们采用逐步提高培养基中的乙醇浓度的方法,定向驯化酿酒酵母实验菌株W303-1A,经过45天的短期定向驯化获得乙醇耐受表型显著提高的突变株EA,它能在含有8%(v／v)乙醇的培养基中保持较高的生长速率,而对照菌株几乎不生长。采用SAGE表达谱(serial analysis of gene expression)分析研究了乙醇适应突变株EA与原始菌株W303-1A在完全培养基和含乙醇压力培养基中的基因表达变化。通过聚类分析可以看出,每组的上调和下调基因分别聚类在不同的区域。EA与W303-1A即使在不含乙醇的完全培养基中的基因表达模式存在明显差异,一些在W3031A中表现为乙醇压力响应表达的基因,女(?)SSA4、OLE1、HXK1在EA中表现为组成型表达。EA与W303-1A分别在乙醇压力下的基因表达变化也不相同,说明压力响应和压力适应机制是不同的过程,它们分别影响不同基因的表达水平。从基因表达水平上反映了驯化株EA乙醇耐受提高的分子基础。对差异表达基因进行了GO (gene ontology)归类分析、途径富集分析和蛋白相互作用网络分析。GO功能分析发现,这些基因分布在包括细胞膜、细胞质、细胞核、线粒体、液泡、蛋白酶复合体等几乎全部的细胞组分,发挥的分子功能集中在各种蛋白结合活性、酶活性的调节、核糖核酸酶活性等方面,参与运输、合成、代谢、氧化磷酸化、内吞作用等多个生物过程。途径富集分析显示,长链不饱和脂肪酸合成途径在对乙醇压力响应时的W303-1A和无压力时的EA与W303-1A差异表达分析中的富集度都较大,而且它们的共同差异表达基因在两组中的表达模式相同。尤其是编码delta (9)脂肪酸去饱和酶基因OLE1,它在W303-1A的乙醇压力响应状态下和EA无压力时都得到上调。酿酒酵母细胞中的两种主要的单不饱和脂肪酸棕榈油酸(／Δ9z-C16：1)和油酸(Δ9z-C18：1)都是由编码OLE1蛋白所催化,它们对维持乙醇压力下的细胞膜稳定性具有重要作用。W303-1A在乙醇压力响应条件下,包括含硒氨基酸代谢、甘氨酸、丝氨酸和苏氨酸代谢以及半胱氨酸代谢等多个氨基酸的代谢途径都受到显著的影响。而EA中只有含硒氨基酸代谢与赖氨酸代谢途径中的相关基因受到影响。W303-1A与EA在乙醇压力响应下的差异表达基因富集度最高的是核糖体蛋白合成途径。在乙醇压力下,EA中核糖体蛋白表达的上调,大大补充了细胞内基因表达翻译所需要的翻译元件,使细胞在压力胁迫下仍旧能够相对高效地组织内部的基因表达系统,促进功能基因的合理高效表达。通过差异表达基因蛋白相互作用分析,获得一个高连接度蛋白HSP82,对其在耐受乙醇的适应性驯化过程中发挥潜在的作用进行深入讨论。在进行酵母实验菌株的全局转录机制工程的同时,我们首次把gTME的方法引入二倍体工业酵母菌株,充分利用酵母自身的同源重组能力和G418抗性筛选标记,采用两步法先敲除基因组上一个拷贝的SPTl5基因,并将等位突变基因SPT15-300整合至基因组上同一位点。借助外源质粒表达受GAL诱导的CRE酶,专一性的切割KanMX敲除元件的loxp序列,去除外源筛选标记,只保留一个长度在21 bp的loxp序列。在不引入外源质粒或基因的前提下,实现基因的定点改造。通过生长表型比较,SPT15-300重组菌在乙醇和葡萄糖组合压力条件下抗性提高,30%葡萄糖高浓度发酵72 h得到乙醇浓度比对照提高43%。模拟工业啤酒发酵条件,以20%麦芽糖葡萄糖混合糖发酵得到乙醇浓度是对照的2倍,大大降低了发酵液中的残糖含量。最后,结合定向驯化的方法,经过短期的适应性驯化,同一批次乙醇发酵,驯化株QA的乙醇产量提高15%。采用定向驯化,进一步提高了菌株的乙醇耐受能力和发酵水平。本论文通过定向驯化得到乙醇耐受性显著提高的突变株,采用SAGE表达谱分析的方法深入研究了驯化株与对照菌株在完全培养基和含乙醇压力培养基中基因表达的变化,对乙醇耐受的分子机制进行了初步探索。采用gTME与定向驯化相结合显著提高了工业菌株的高浓度发酵水平。本论文对酿酒酵母耐乙醇机制的研究和高浓度发酵具有重要的理论和实际意义。更多还原

【Abstract】 Saccharomyces cerevisiae, as the most human related species, has quite extensive applications during the history of human beings. Very high gravity fermentation (VHGF) can reach a relative high ethanol concentration in the same equipment and time scale, making the cost down, VHGF has recently draw brewer’s attention due to its advantage of energy, laboring and space saving. However, high concentrations of carbohydrate initially in VHGF can bring osmotic pressure to cells inhibiting its specific growth rate and production activity. Besides, the gradual increased ethanol produced along fermentation affected cell growth and even made fermentation stuck. Given this, it is requisite that yeast strains used for VHGF should possess superior tolerance properties.Although many efforts have been devoted to elicit these properties, the adaptation and response mechanisms to stresses still have not been fully understood till now. Meanwhile, industrial diploid strains possess different genetic background and higher stress resistance than the laboratory haploid strains. It is difficult to enhance yeast tolerance only by modifying one or two target genes, especially for industrial strains with naturally sophisticated ethanol tolerance and productivity.Transcription initiation by RNA polymerase II involves the assembly of general transcription factors on the core promoter to form a preinitiation complex (PIC), which contains several General/basal transcription factors (GTF’s), named TFⅡA、TFⅡB、TFⅡC、TFⅡD、TFⅡF和TFⅡH. All of them constitute a complex of about 2MDa. TFIID is a multi-subunit complex consisting of TBP and a set of TBP-associated factors (TAFs). The first step in PIC assembly is binding of the TATA-box-binding protein (TBP) or TFIID to the TATA box. Transcriptional activators bind to specific cis-acting promoter elements within upstream activating sequences (UASs)/enhancers and stimulate PIC assembly through a mechanism thought to involve direct interactions with one or more components of the transcription machinery. The communication between the enhancer-bound activators and the basal transcription machinery depends on a third class of transcription factors, the so-called coactivators. Each gene is controlled by a unique array of binding sites for distinct activators that ensure its expression at the right time and place.The tremendous complexity of dynamic interactions in cellular systems often impedes practical applications of metabolic engineering that are largely based on available molecular or functional knowledge. Global transcription machinery engineering (gTME) is a new cellular engineering concept advocated by Alper and Stephanopoulos, which aims to modify the transcription factor behavior to reprogram a series of gene transcription. It enables multiple, simultaneous perturbations at genomic level.In contrast, evolutionary engineering follows nature’s’engineering’ principle by variation and selection. Thus, it is a complementary strategy that offers compelling scientific and applied advantages for strain development and process optimization, provided a desired phenotype is amenable to direct or indirect selection. In addition to simple empirical strain development by random mutation and direct selection on plates, evolutionary engineering also encompasses recombination and continuous evolution of large populations over many generations. Two distinct evolutionary engineering applications are likely to gain more relevance in the future:first, as an integral component in metabolic engineering of strains with improved phenotypes, and second, to elucidate the molecular basis of desired phenotypes for subsequent transfer to other hosts. The latter will profit from the broader availability of recently developed methodologies for global response analysis at the genetic and metabolic level. These methodologies facilitate identification of the molecular basis of evolved phenotypes. It is anticipated that, together with novel analytical techniques, bioinformatics, and computer modeling of cellular functions and activities, evolutionary engineering is likely to find its place in the metabolic engineer’s toolbox for research and strain development.The major results of the thesis are as follows:gTME was applied in a standard strain by a centromeric plasmid. SPT15-300 was expressed under the control of a constitutive promoter PTEF. Strains expressing SPT15 as control, cell growth phenotype was compared under different combined stress conditions with elevated ethanol/glucose concentrations. To our disappointed, the strain expressed SPT15-300 showed marginally improved. This is likely related to the media containing plenty of nutrition. The impacts of SPT15-300 to yeast exhibited its complexity.While gTME made little sense to standard strains, directed evolution was adopted by guadual increasing ethanol concentration for about 45 days. A mutant holding eleviated ethanol tolerance was obtained, which could grow under media with 8% ethanol, while the control did not grow at all. Following that, serial analysis of gene expression (SAGE) was performed to analysis differential expression genes under YPD containing no or 6% ethanol for the adapted strain and its parent strain. By clustering of these differential expression genes, we got distinct gene clustering modules for each sample, with up-regulated and down-regulated genes in different region. This implied that EA and W303-1A showed differential gene expression module even under no stress condition. Some genes, such as SSA4, OLE1, HXK1, showed constitutive expression in EA. Furthermore, gene expression under ethanol stress for EA and W303-1A also showed diversity.Gene ontology (GO), pathway analysis and protein-protein interaction network were carried out. Genes involved in plasma membrane, cytoplasm, cell wall, nucleolus, mitochondrion, vacuole and proteasome complex all showed differential expression. They participated in protein binding, enzyme regulator activity, ribonuclease activity, and transport, biosynthetic and metabolic proces, oxidative phosphorylation, endocytosis and so on. As for pathway, polyunsaturated fatty acid biosynthesis and amino acid metabolism showed remarkably enriched under ethanol response. Especially, the OLE1 gene,which is vital for polyunsaturated fatty acid biosynthesis, showed up-regulated both under ethanol reponse of W303-1A and under no stress of EA. Genes involved in ribosome protein synthesis were consistent up-regulated in EA under ethanol response, making it more robust under stress. By network analysis, a gene coding protein, HSP82 was significantly interacted, which is consistent with its role in protein network.For the first time, gTME was also applied into the industrial brewer yeast with two steps of homologous recombination without introducing additional exogenous genes or plasmid, which resulting in a similar growth phenotype in the same condition as reported by Baerends et al. However, we found that the fermentation performance of the engineered strain was improved under high gravity conditions.A mutant with excellent ethanol tolerance was obtained. And gene differential expression was carried out by SAGE analysis between the mutant and its parents, which interpreted the molecular mechanism underlining the changes of ethanol tolerance. Combined gTME and directed evolution, the performance was improved distinctly under VHGF. All of these have potential applications both in understanding ethanol tolerance and VHGF.更多还原